Attention mechanism can be viewed as a tool that can allocate available resources to the most informative part of the input. In order to improve the efficiency during the learning procedure, some works are proposed to guide the network to pay more attention to the regions of interest. For instance, Hu et al. [1]} proposed a squeeze-and-excitation (SE) block to model channel-wise relationships in the image classification task. Wang et al. [2]} proposed a non-local attention neural network for video classification by incorporating non-local operations. Motivated by these methods, attention mechanism has also been introduced into SISR.
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